A neural-based electromagnetic inverse scattering approach to the detection of a conducting cylinder coated with a dielectric material

被引：0

作者：

Makal, Senem ^{[1
]}

Kizilay, Ahmet ^{[1
]}

机构：

[1] Yildiz Tech Univ, Fac Elect & Elect Engn, Dept Elect & Commun Engn, TR-34349 Istanbul, Turkey

来源：

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES | 2012年 / 20卷

关键词：

Electromagnetic scattering; the method of moment; neural network; inverse scattering; NETWORK APPROACH; LAYERED MEDIA;

D O I：

10.3906/elk-1009-789

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material. A set of features, the radar cross-section (RCS) values, are derived from scattered fields, which are calculated using the surface equivalence principle and the method of moment. RCS values are obtained using 10 different scattering angles that are fed into the network. The outputs of the network are the location (x(0), y(0)) and the radius (r(p)) of the conducting cylinder. This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

引用

页码：1249 / 1258

页数：10

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